{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f0f3dc62-64df-4b58-893b-f7b1a34ed8bb",
   "metadata": {},
   "source": [
    "Chapter 09\n",
    "\n",
    "# 高斯朴素贝叶斯分类\n",
    "Book_7《机器学习》 | 鸢尾花书：从加减乘除到机器学习"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f0827fa5-15c4-4ebe-a3c9-57204493aefd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.colors import ListedColormap\n",
    "from sklearn import datasets\n",
    "from sklearn.naive_bayes import GaussianNB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "555572e2-5ce1-4b4e-956e-c2ebdcd61af0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the iris data\n",
    "iris = datasets.load_iris()\n",
    "\n",
    "# Only use the first two features: sepal length, sepal width\n",
    "X = iris.data[:, 0:2]\n",
    "y = iris.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "38237f16-d854-4213-8aab-de3e55aaa5e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# generate mesh\n",
    "h = .02  # step size in the mesh\n",
    "x1_min, x1_max = X[:, 0].min() - 0.2, X[:, 0].max() + 0.2\n",
    "x2_min, x2_max = X[:, 1].min() - 0.2, X[:, 1].max() + 0.2\n",
    "xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, h),np.arange(x2_min, x2_max, h))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a92913c8-f3a6-48cc-bfa8-185b16d54f9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create color maps\n",
    "rgb = [[255, 238, 255],  # red\n",
    "       [219, 238, 244],  # blue\n",
    "       [228, 228, 228]]  # black\n",
    "rgb = np.array(rgb)/255.\n",
    "\n",
    "cmap_light = ListedColormap(rgb)\n",
    "cmap_bold = [[255, 51, 0], [0, 153, 255],[138,138,138]]\n",
    "cmap_bold = np.array(cmap_bold)/255."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d80c422b-9f02-4bc5-a244-5933e05562c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# GaussianNB implements the Gaussian Naive Bayes algorithm\n",
    "gnb = GaussianNB()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2d62611c-8831-409b-9a28-1c44f03a1509",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>GaussianNB()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">GaussianNB</label><div class=\"sk-toggleable__content\"><pre>GaussianNB()</pre></div></div></div></div></div>"
      ],
      "text/plain": [
       "GaussianNB()"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit the data\n",
    "gnb.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b91c5a94-9b7a-44c8-968e-5ff5451d4caf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# query points\n",
    "q = np.c_[xx1.ravel(), xx2.ravel()];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6dfd9cd4-82ac-4dae-8fd5-2f7d023ca4a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Predict; query points are the meshgrid points\n",
    "y_predict = gnb.predict(q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "88fcbcf0-f84a-4d54-bbe2-87a750f0191a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Put the result into a color plot\n",
    "y_predict = y_predict.reshape(xx1.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7161b01d-090d-43df-8820-296e0d1eef03",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\james\\anaconda3\\lib\\site-packages\\seaborn\\_oldcore.py:200: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
      "  if palette in QUAL_PALETTES:\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualization\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# plot decision regions\n",
    "plt.contourf(xx1, xx2, y_predict, cmap=cmap_light)\n",
    "\n",
    "# plot decision boundaries\n",
    "plt.contour(xx1, xx2, y_predict, levels=[0,1,2], colors=np.array([0, 68, 138])/255.)\n",
    "\n",
    "# Plot data points\n",
    "sns.scatterplot(x=X[:, 0], y=X[:, 1], hue=iris.target_names[y],\n",
    "                palette=cmap_bold, alpha=1.0, \n",
    "                linewidth = 1, edgecolor=[1,1,1])\n",
    "\n",
    "# Figure decorations\n",
    "plt.xlim(xx1.min(), xx1.max())\n",
    "plt.ylim(xx2.min(), xx2.max())\n",
    "plt.title(\"Gaussian Naive Bayes\")\n",
    "plt.xlabel(iris.feature_names[0])\n",
    "plt.ylabel(iris.feature_names[1])\n",
    "ax.grid(linestyle='--', linewidth=0.25, color=[0.5,0.5,0.5])\n",
    "plt.tight_layout()\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
